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Title: Intraspecific trait variation improves understanding and management of cover crop outcomes - Field Experiment Dataset Open Access Deposited

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Methodology
  • We measured maximum plant height for each species by taking the height of five individuals per plot as the distance between the base of the plant shoot and the tallest photosynthetic tissue (Pérez-Harguindeguy et al. 2016). We calculated SLA (fresh leaf surface area divided by its dry mass) following Pérez-Harguindeguy et al. (2016) and Garnier et al. (2001) for five leaves from each of five individuals per plot, and used ImageJ software to determine surface area. Leaf N concentrations were analyzed using the leaves collected for SLA. Dried leaf samples were ground to < 2mm and processed for % N by dry combustion on a Leco TruMac CN Analyzer (Leco Corporation, St. Joseph MI). To calculate each species’ C:N ratio in each treatment, aboveground biomass was also ground to < 2mm and analyzed for % C and N on a Leco TruMac CN Analyzer. Aboveground biomass sampling is detailed below. Date of flower emergence was recorded as a potentially plastic trait for the two broadleaf species (CWP and BWT) for all of the plots in which they were present.

  • To determine root:shoot ratios for CWP and SDX in monoculture and in the two-species mixture, five plants per species per plot were excavated at random. We standardized their removal by digging 30-cm diameter holes centered around each plant. Given the species under consideration and the short length of the summer cover crop growing season, we expected this procedure to provide an adequate estimate of root biomass for making treatment comparisons. After gently washing roots to remove adhering soil, roots and shoots were separated and dried in a forced-air oven at 60° C for 48 hr. Dry weights were used to calculate a root:shoot ratio for each plant.

  • Aboveground biomass was sampled from a 0.25 m2 quadrat placed randomly within each plot, at least 0.5 m from the edge. Shoot components were clipped at the ground, separated by species (weeds were grouped into one category), then dried at 60° C for 48 hr, and weighed to measure aboveground biomass production. Aboveground weed biomass samples were then used to calculate the percentage of weeds suppressed by each of the cover crop treatments, as compared to the weed biomass in the control. Weed suppression was quantified as: (Wc – Wt)/Wc * 100 where Wc is mean aboveground weed biomass in the weedy fallow control plots, and Wt is mean aboveground weed biomass in each cover crop treatment. To estimate aboveground N assimilation, N concentrations for aboveground biomass samples were multiplied by aboveground biomass for each species in a given treatment. Belowground N assimilation was approximated using root samples collected for the root:shoot measurements. Specifically, dried root samples were ground to < 2mm and analyzed for % N by dry combustion. We then used the root:shoot ratios to approximate the proportion of biomass allocated belowground and multiplied this biomass estimate by root % N for each species to calculate belowground N assimilation. We estimated total plant N assimilation by summing above- and below-ground N assimilation. For mixtures, we summed the N contents for each component species to determine the amount of N assimilated in kg N ha-1 at the community level.

  • We measured potentially leachable NO3- during the cover crop season (i.e., NO3- below the rooting zone) with anion exchange resin bags, by adapting the methods in Finney et al. (2016). On 16 June, 2017, two 13x13 cm bags per plot, each containing 100 mL of moist resin beads (Purolite A-400, Purolite Corporation, Philadelphia PA), were buried to approximately 0.3 m, with bags oriented parallel to the soil surface. Bags were removed on 28 July, 2017 from the BWT monocultures along with one of the two bags in the control plots, while all other resin bags were removed on 10 August, 2017. Beads were extracted twice with 300 mL 2M KCl. Whatman 42 filter papers were used to filter each extraction before freezing until analysis. Extraction efficiency was estimated at 89.5%. NO3- concentration of the extracted samples was analyzed on an AQ2 Discrete Analyzer (Seal Analytical Inc., Mequon WI). We calculated potentially leachable NO3- (hereafter referred to as PLN) using the equation detailed in Finney et al. (2016), with a resin bag area of 0.017 m2.

  • Statistical analyses were performed in R (The R Foundation for Statistical Consulting, Vienna, Austria, v3.5.1). SLA and leaf N trait values were log-transformed to meet assumptions of normality before analysis. We calculated descriptive statistics for each trait and species across treatments, using coefficients of variation (CV) to assess the extent of ITV. We then performed one-way analysis of variance (ANOVA), with treatment and block as fixed effects, to detect significant differences in functional trait expression between monocultures and mixtures for CWP and SDX, while Student’s t-tests were used to compare trait expression for BWT between monoculture and mixture. We used the same ANOVA model to test for significant differences in ecosystem services between treatments. Where significant differences were identified by ANOVA tests, Tukey’s honestly significant difference (HSD) was used for mean comparisons. Results were determined significant at α ≤ 0.05, or ecologically-relevant at α ≤ 0.10. We used Pearson’s correlation coefficients to assess relationships between functional traits and ecosystem services across all treatments. Because the ANOVA results indicated significant treatment differences only occurred for aboveground and total N assimilation services, we focused on these for exploring trait-service relationships. We first assessed relationships at the community level in accordance with common practice for studies involving cover crop mixtures, and then at the individual level using trait values for each species. For community-level relationships, we used community-weighted mean (CWM) trait values, which were weighted using aboveground biomass for each species in mixture.

  • References: Finney, D.M., White, C.M. and Kaye, J.P. (2016). Biomass production and carbon/nitrogen ratio influence ecosystem services from cover crop mixtures. Agronomy Journal, 108(1), pp.39-52. Garnier, E., Shipley, B., Roumet, C. and Laurent, G. (2001). A standardized protocol for the determination of specific leaf area and leaf dry matter content. Functional ecology, 15(5), pp.688-695. Perez-Harguindeguy, N., Diaz, S., Garnier, E., Lavorel, S., Poorter, H., Jaureguiberry, P., Bret-Harte, M.S., Cornwell, W.K., Craine, J.M., Gurvich, D.E. and Urcelay, C. (2016). Corrigendum to: new handbook for standardised measurement of plant functional traits worldwide. Australian Journal of botany, 64(8), pp.715-716.
Description
  • This data was produced as part of field experiment investigating the extent, drivers, and consequences of functional trait variation in cover crops. Specifically, we studied the role of intraspecific trait variation in explaining interactions between species in cover crop mixtures, and whether and how intraspecific trait variation improves understanding of relationships between functional traits and ecosystem services from cover crops.
Creator
Depositor
  • herricke@umich.edu
Contact information
Discipline
Keyword
Citations to related material
  • Herrick, E., and Blesh, J. (2021) Intraspecific trait variation improves understanding and management of cover crop outcomes. Ecosphere.
Resource type
Last modified
  • 11/19/2022
Published
  • 06/18/2021
Language
DOI
  • https://doi.org/10.7302/bbwb-z988
License
To Cite this Work:
Herrick, E. M. (2021). Intraspecific trait variation improves understanding and management of cover crop outcomes - Field Experiment Dataset [Data set], University of Michigan - Deep Blue Data. https://doi.org/10.7302/bbwb-z988

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